An Efficient Algorithm for Designing Optimal CRCs for Tail-Biting Convolutional Codes

16 Jan 2020  ·  Hengjie Yang, Linfang Wang, Vincent Lau, Richard D. Wesel ·

This paper proposes an efficient algorithm for designing the distance-spectrum-optimal (DSO) cyclic redundancy check (CRC) polynomial for a given tail-biting convolutional code (TBCC). Lou et al. proposed DSO CRC design methodology for a given zero-terminated convolutional code (ZTCC), in which the fundamental design principle is to maximize the minimum distance at which an undetectable error event of ZTCC first occurs. This paper applies the same principle to design the DSO CRC for a given TBCC. Our algorithm is based on partitioning the tail-biting trellis into several disjoint sets of tail-biting paths that are closed under cyclic shifts. This paper shows that the tail-biting path in each set can be constructed by concatenating the irreducible error events and/or circularly shifting the resultant path. This motivates an efficient collection algorithm that aims at gathering irreducible error events, and a search algorithm that reconstructs the full list of error events in the order of increasing distance, which can be used to find the DSO CRC for a given TBCC.

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